Abstract [en]

This article addresses the issue of measuring uncertainty in optimization problems arising in system identification. The issue of uncertainty has been studied in the theory of risk, where the results are mainly employed in finance applications. Here we explore how the results in the literature of theory of risk can be used to obtain a systematic approach to uncertainty in system identification. For concreteness, the discussion is illustrated by an application to input design, but it can be extended to other areas of the field.